The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.
Multi-source information fusion based fault diagnosis of ground-source heat pump using Bayesian network
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Citations
Cites
(2017) · Encyclopedia of Machine Learning and Data Mining · doi:10.1007/978-1-4899-7687-1_100245 · Cited by 1,424
Advances in heat pump systems: a review
Chua, K. J., Chou, S. K., & Yang, W. M. (2010) · Applied Energy · doi:10.1016/j.apenergy.2010.06.014 · Cited by 966
Achieving better energy-efficient air conditioning – A review of technologies and strategies
Chua, K. J., Chou, S. K., Yang, W. M., & Yan, J. (2013) · Applied Energy · doi:10.1016/j.apenergy.2012.10.037 · Cited by 949
Overview on Bayesian networks applications for dependability, risk analysis and maintenance areas
Weber, P., Medina-Oliva, G., Simon, C., & Iung, B. (2012) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2010.06.002 · Cited by 765
Geothermal heat pump systems: Status review and comparison with other heating options
Self, S. J., Reddy, B. V., & Rosen, M. A. (2013) · Applied Energy · doi:10.1016/j.apenergy.2012.01.048 · Cited by 602
Bayesian networks in reliability
Langseth, H., & Portinale, L. (2007) · Reliability Engineering & System Safety · doi:10.1016/j.ress.2005.11.037 · Cited by 571
Mohanraj, M., Jayaraj, S., & Muraleedharan, C. (2012) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2011.10.015 · Cited by 419
Vagis, A. A. (2002) · Journal of Automation and Information Sciences · doi:10.1615/jautomatinfscien.v34.i6.40 · Cited by 404
An intelligent chiller fault detection and diagnosis methodology using Bayesian belief network
Zhao, Y., Xiao, F., & Wang, S. (2012) · Energy and Buildings · doi:10.1016/j.enbuild.2012.11.007 · Cited by 215
Wang, S., & Cui, J. (2005) · Applied Energy · doi:10.1016/j.apenergy.2004.11.002 · Cited by 200
Cited by
Improving the accuracy of medical diagnosis with causal machine learning
Richens, J. G., Lee, C. M., & Johri, S. (2020) · Nature Communications · doi:10.1038/s41467-020-17419-7 · Cited by 598
Zhao, Y., Li, T., Zhang, X., & Zhang, C. (2019) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2019.04.021 · Cited by 594
Bayesian Networks in Fault Diagnosis
Cai, B., Huang, L., & Xie, M. (2017) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2017.2695583 · Cited by 474
Self-citationWang, Z., Wang, Z., He, S., Gu, X., & Yan, Z. F. (2017) · Applied Energy · doi:10.1016/j.apenergy.2016.11.130 · Cited by 138
Metadata
- Authors
- Cai, B., Liu, Y., Fan, Q., Zhang, Y., Liu, Z., Yu, S., & Ji, R.
- Venue
- Applied Energy
- Publisher
- Elsevier BV
- Published
- 2014-02
- Volume
- 114
- Pages
- 1-9
- ISSN
- 0306-2619 (ISSN-L)
- OpenAlex
- W2014540231
- Cited by
- 329
- References
- 27
- FWCI
- 15.34
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Multi-source information fusion based fault diagnosis of ground-source heat pump using Bayesian network. https://app.cochat.ai/papers/10.1016/j.apenergy.2013.09.043
- The paper
- Cai, B., Liu, Y., Fan, Q., Zhang, Y., Liu, Z., Yu, S., & Ji, R. (2014). Multi-source information fusion based fault diagnosis of ground-source heat pump using Bayesian network. Applied Energy. https://doi.org/10.1016/j.apenergy.2013.09.043
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
